Viewer authentication

ABSTRACT

Apparatus, systems, articles of manufacture, and methods for viewer authentication are disclosed. An example system includes processing circuitry to execute computer readable instructions to send one or more instructions to cause the user device to: trigger collection of audio metering data from a sensed audio signal based on a programming schedule that is to identify when the program is to be broadcast; accept voting data from the user for a ballot presented in the program; transmit the audio metering data; and transmit the voting data. The processing circuitry also is to determine a level of exposure of the user to the program based on the audio metering data received from the user device; calculate a weighting score based on the level of exposure; and adjust the voting data based on the weighting score.

RELATED APPLICATION

This patent arises from a continuation of U.S. patent application Ser.No. 16/353,041, which was filed on Mar. 14, 2019. Priority is claimed toU.S. patent application Ser. No. 16/353,041. U.S. patent applicationSer. No. 16/353,041 is hereby incorporated by reference in its entirety.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience detection and, moreparticularly, to viewer authentication.

BACKGROUND

Some broadcasts of competition programs prompt viewers to vote for acontestant. Some programs accept votes from a person who may not havebeen a viewer.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example system for viewer authenticationthat includes an example user device and example remote center.

FIG. 2 is a flowchart representative of machine readable instructionswhich may be executed to implement the example user device of FIG. 1.

FIG. 3 is a flowchart representative of machine readable instructionswhich may be executed to implement the example remote center of FIG. 1.

FIG. 4 is a block diagram of an example processing platform structuredto execute the instructions of FIG. 2 to implement the example userdevice of FIG. 1.

FIG. 5 is a block diagram of an example processing platform structuredto execute the instructions of FIG. 3 to implement the example remotecenter of FIG. 1.

The figures are not to scale. Also, in general, the same referencenumbers will be used throughout the drawing(s) and accompanying writtendescription to refer to the same or like parts.

Descriptors “first,” “second,” “third,” etc. are used herein whenidentifying multiple elements or components which may be referred toseparately. Unless otherwise specified or understood based on theircontext of use, such descriptors are not intended to impute any meaningof priority, physical order or arrangement in a list, or ordering intime but are merely used as labels for referring to multiple elements orcomponents separately for ease of understanding the disclosed examples.In some examples, the descriptor “first” may be used to refer to anelement in the detailed description, while the same element may bereferred to in a claim with a different descriptor such as “second” or“third.” In such instances, it should be understood that suchdescriptors are used merely for ease of referencing multiple elements orcomponents.

DETAILED DESCRIPTION

Multiple broadcast competition or contest programs include viewer votingresults as part of the full scoring criteria for the contest.Broadcasting a program includes transmission of a program via televisionor radio or streaming a program over the Internet. Social media makes itpossible for viewer votes to be cast by people who never actually watchthe program, i.e., non-viewers. These non-viewers may be prompted tovote after seeing a post on a social media platform by the contestant, asocial media influencer, or other users of the social media platform.Voting by non-viewers can skew the results and lead to a lack ofconfidence in the scoring system. This disclosure is directed toimproving the quality of viewer voting results for broadcast contestprograms. Throughout this disclosure, the nouns “broadcast contestprogram”, “contest program,” “competition program,” “broadcast,”“program”, “programming,” and “show” are used interchangeably.

The techniques disclosed herein confirm that a vote being cast for acontest program corresponds to an actual viewer of the program. In somedisclosed examples, a mobile application is executed by a smartphone,tablet, or other mobile device. In other examples, an application orother software program may be run on a desktop computer or othercomputing device. The term “mobile application” is used herein to referto any application or software program running on any type of computingdevice that is programmed and/or structured to operate in accordancewith the teachings of this disclosure. Also, throughout this disclosure,“user,” “operator”, and “voter” may be used interchangeably. “Viewer”and “non-viewer” are used to specify a user, operator, or voter based onexposure to a contest program or other media. In addition, the term“viewer” is meant to encompass listeners of radio programs and/orlisteners of television programs and/or internet streaming who areexposed to programs but may not have visually consumed the programs.Similarly, the term “non-viewer” is meant to encompass non-listeners.

The mobile application provides an interface to enable a user to votefor a contestant in a broadcast contest program. In some examples, themobile application sensed the background audio to gather audio signalsbroadcast in the contest program. The mobile application samples andanalyzes the audio signals to detect watermarks that are broadcast inthe audio signals of the contest program and/or to generate signaturesfrom the audio signals of the contest program. In such examples, theconfirmation of the voter as a viewer is an authentication using audiowatermarking and/or signaturing.

Audio watermarking is a technique used to identify media such astelevision broadcasts, radio broadcasts, advertisements (televisionand/or radio), downloaded media, streaming media, prepackaged media,etc. Some audio watermarking techniques identify media by embedding oneor more audio codes (e.g., one or more watermarks), such as mediaidentifying information and/or an identifier that may be mapped to mediaidentifying information, into an audio and/or video component. In someexamples, the audio or video component is selected to have a signalcharacteristic sufficient to hide the watermark. As used herein, theterms “code” or “watermark” are used interchangeably and are defined tomean any identification information (e.g., an identifier) that may beinserted or embedded in the audio or video of media (e.g., a program oradvertisement) for the purpose of identifying the media or for anotherpurpose such as tuning (e.g., a packet identifying header). As usedherein “media” refers to audio and/or visual (still or moving) contentand/or advertisements. To identify watermarked media, the watermark(s)are extracted and used to access a table of reference watermarks thatare mapped to media identifying information.

Unlike media monitoring techniques based on codes and/or watermarksincluded with and/or embedded in the monitored media, fingerprint orsignature-based media monitoring techniques generally use one or moreinherent characteristics of the monitored media during a monitoring timeinterval to generate a substantially unique proxy for the media. Such aproxy is referred to as a signature or fingerprint, and can take anyform (e.g., a series of digital values, a waveform, etc.) representativeof any aspect(s) of the media signal(s)(e.g., the audio and/or videosignals forming the media presentation being monitored). A signature maybe a series of signatures collected in series over a timer interval. Agood signature is repeatable when processing the same mediapresentation, but is unique relative to other (e.g., different)presentations of other (e.g., different) media. Accordingly, the term“fingerprint” and “signature” are used interchangeably herein and aredefined herein to mean a proxy for identifying media that is generatedfrom one or more inherent characteristics of the media.

Signature-based media monitoring generally involves determining (e.g.,generating and/or collecting) signature(s) representative of a mediasignal (e.g., an audio signal and/or a video signal) output by amonitored media device and comparing the monitored signature(s) to oneor more references signatures corresponding to known (e.g., reference)media sources. Various comparison criteria, such as a cross-correlationvalue, a Hamming distance, etc., can be evaluated to determine whether amonitored signature matches a particular reference signature. When amatch between the monitored signature and one of the referencesignatures is found, the monitored media can be identified ascorresponding to the particular reference media represented by thereference signature that with matched the monitored signature. Becauseattributes, such as an identifier of the media, a presentation time, abroadcast channel, etc., are collected for the reference signature,these attributes may then be associated with the monitored media whosemonitored signature matched the reference signature. Example systems foridentifying media based on codes and/or signatures are long known andwere first disclosed in Thomas, U.S. Pat. No. 5,481,294, which is herebyincorporated by reference in its entirety.

In some examples, the mobile application supports live or real timevoting in which voting occurs during the broadcast. In some examples,for signature generation, the mobile application can maintain a bufferof a predetermined amount of time of the program such as, for example, Xminutes. The mobile application returns the signatures(s) and/ordetected watermark(s) with the ballot cast by the voter to a back officeor remote, central center where the voters are authenticated and votesare tallied.

In some examples, the mobile application supports delayed voting inwhich voting occurs after the program is broadcast. In such examples,the mobile application samples the sensed background audio signals todetect watermarks and/or generate signatures during the broadcast timeof the program (e.g., based on a program schedule downloaded to theapplication). The mobile application stores the signatures(s) and/ordetected watermark(s), and then reports the storedsignatures(s)/watermark(s) with the ballot later cast by the voter.

In either example, the back office analyzes thesignature(s)/watermark(s) reported with any user votes to determinewhether the signature(s)/watermark(s) correspond to the broadcastcontest program and, thus, the voter was actually exposed to the program(e.g., as compared to voting based on social media influencing withoutactually having viewed the program). If the signature(s)/watermark(s)reported with a viewer's ballot correspond to the broadcast contestprogram, the vote is given higher weight than another vote that does nothave any signature(s)/watermark(s) corresponding to the broadcastcontest program. In some examples, votes corresponding to people who arenon-viewers may be voided.

Turning to the figures, FIG. 1 is a block diagram of an example system100 for viewer authentication that includes an example user device 102and example remote center 104. The example user device 102 is acomputing device such as, for example, a computer, a tablet, a mobilephone, a smart watch, etc. The example user device 102 includes anexample sensor 106, an example clock 108, an example scheduler 110, anexample trigger 112, an example sampler 114, an example database 116, anexample user input 118, an example analyzer 120, an example decoder 122,an example receiver 124, and an example transmitter 126. The exampleremote center 104 may be a computing center such as, for example, a backoffice processing center at a broadcast studio, an accounting firm, anaudience measurement entity, or other entity. The example remote center104 includes an example data input 128, an example comparator 130, anexample library 132, an example calculator 134, an example authenticator136, an example tallier 138, and an example output 140.

A person or user operating the user device 102 installs the mobileapplication that provides viewer authentication for voting in broadcastcontest programs. The mobile application may be installed to the userdevice 102 via the receiver 124. In some examples, the mobileapplication is received from the remote center 104. In other examples,the mobile application is received from another entity such as, forexample, an application library including, for example, an app store. Insome examples, the mobile application of the user device 102 receives aschedule of broadcast programming via the scheduler 110. The schedulemay be saved, for example, in the database 116. The user provides inputvia the user input 118 including, for example, selection of aprogramming schedule for broadcast contest programs the user wants toview and/or to submit votes. In other examples, the user is able toparticipate in a competition voting without preselection of aprogramming schedule.

The clock 108 maintains timing of the user device 102 in accordance withthe time of day. The clock 108 works in concert with the scheduler 110to develop a schedule for the mobile application. Based on the time ofday kept by the clock and the schedule imported into the scheduler 110,the trigger 112 triggers or begins sensing and collection of audiosignals. For example, when the clock 108 indicates that the time of dayis approaching a broadcast time for a contest program selected by theuser based on the broadcast schedule imported by the scheduler 110, thetrigger 112 triggers the sensor 106 to sense and collect audio signals.

In some examples, the sensor 106 includes a microphone to sense andcollect audio signals from the environment of the user device 102. Forexample, the sensor 106 collects the background audio from a room inwhich the user device 102 is located. The sensor 106 gathers audiosignals from the contest program if the user device 102 is located neara television, computer, tablet, or other source presenting the contestprogram. In some examples, the sensor 106 is an array of microphones. Inother examples, the sensor 106 can be any device capable of gatheringaudio signals.

In some examples, the sampler 114 samples the audio signals. Audiosignal sampling includes signal processing such as, for example,reducing a continuous time signal to a discrete time signal,analog-to-digital conversion, and/or conversion of the audio signal intofrequency components, for example, by Fast Fourier Transform (FFT),wavelet transform, or other time-to-frequency domain transformation.

The analyzer 120 reviews the sampled audio signals. In some examples,the analyzer 120 generates signatures from the audio signals. In otherexamples, the analyzer 120 includes the decoder 122, which decodes theaudio signals to detect watermarks in the audio signals. In theseexamples, the analyzer 120 extracts audio metering data, which includesthe signatures and/or the watermarks, from the audio signal. As detailedabove, the audio metering data provides evidence of the programmingpresented in the environment of the user device 102 and sensed by thesensor 106. In some examples, the audio metering data is stored in abuffer, for example, the database 116.

In some examples, the schedule receiver 110 accepts, receives, orretrieves program schedules for contest programs, reference watermarks,and reference signatures. The program schedules for contest programs,reference watermarks, and reference signatures individually orcollectively form broadcast data.

The broadcast data can be used to identify a program. For example, theanalyzer 120 can perform a comparison of the audio metering data and thebroadcast data. Based on the comparison, the analyzer 120 can determineif the audio metering data matches a program identified by the broadcastdata. A match between the audio metering data and the broadcast data isevidence that the user of the user of the user device 102 was exposed tothe broadcast program identified by the broadcast data.

During the broadcast of the contest program, the viewer is prompted tovote for a contestant. The viewer can input their vote or ballot intothe user input 118. The ballots or multiple ballots are stored in thedatabase 116 as voting data. In some examples, the voting data is storedin the database 116 with corresponding audio metering data. Also, insome examples, the voting data and the audio metering data aretimestamped.

The transmitter 126 transmits the audio metering data (the signature(s)and/or watermark(s)) and the voting data to the remote center 104 foranalysis and tallying. The transmitter may, in some examples, transmitthe sensed audio signal, one or more portions of the sensed audiosignal, the sampled signal, and/or one or more portions of the sampledsignal instead of the audio metering data. In such examples, the sensedaudio signal is processed at the remote center 104.

In some examples, the audio metering data and the voting data aretransmitted separately and correlated based on timestamps. In otherexamples, the audio metering data and the voting data are transmittedtogether. Also, in some examples, the audio metering data and/or votingdata is transmitted during the broadcast of the contest program. Inother examples, the audio metering data and/or voting data istransmitted on a delayed schedule including, for example, within apredetermined amount of time after the end of the broadcast. Forexample, in some contest programs, a voting period is established for aspecified period of time after the end of the broadcast. In theseexamples, the scheduler 110 may receive an indication of the votingperiod, the clock 108 maintains the timing, and the transmitter 126 maytransmit the audio metering data and/or voting data before theexpiration of the voting period.

In some examples, the sensor 106 implements sensing means, the schedulerimplements scheduling means, the trigger implements triggering means,the sampler implements signal processing means, and the analyzer 120implements processing means. One or more of the sensing means, thescheduling means, the triggering means, the signal processing means,and/or the processing means may be implemented by a processor such asthe processor 412 of FIG. 4 executing instructions such as theinstructions of FIG. 2.

The data input 128 of the remote center 104 accepts, receives, orretrieves the audio metering data and voting data from the user device104. In addition, the data input 128 receives voting data from othersources including, for example, people casting ballots outside of themobile application. In addition, in some examples, the library 132accepts, receives, or retrieves the broadcast data including, forexample, program schedules for contest programs, reference watermarks,and reference signatures. In other examples, as disclosed above, thebroadcast data is alternatively or additionally received and utilized atthe user device 102.

As noted above, the broadcast data is useful for identifying a program.In an examples disclosed above, the analyzer 120 of the user device 102evaluates the audio metering data and the broadcast data to determineexposure by a user casting ballot to a program. In other examples, theevaluation occurs at the remote center 104 where the comparator 130 canaccess the audio metering data received from the user device 102 andaccess the broadcast data representative of a program that is receivedin the library 132. The comparator 130 performs a comparison of theaudio metering data and the broadcast data. Based on the comparison, thecomparator 130 can determine if the audio metering data provided by theuser device matches a program identified by the broadcast data. A matchbetween the audio metering data provided by the user device and thebroadcast data is evidence that the user of the user of the user device102 was exposed to the broadcast program identified by the broadcastdata. In some examples, the authenticator 136 authenticates the user ofthe user device 102 as a viewer based on the match between the audiometering data provided by the user device and the broadcast data.

In some examples, there is no audio metering data corresponding tovoting data because, for example, the person casting the ballot did notuse the mobile application. In such examples, the comparator 130 cannotdetermine a match between audio metering data and broadcast data. Inthis example, the authenticator 136 identifies the user or voter as anon-viewer.

Also, in some examples, the comparator 130 determines a level ofexposure of the user of the user device 102 to the program based on thecomparison of the audio metering data and the broadcast data. Forexample, the user may be exposed to the program for a duration, ormultiple durations that total to less than the total duration of theprogram. This indicates that the user was not a viewer of the entireprogram. In some examples, the comparator 130 determines the amount orlevel of exposure of the user to the program based on the amount ofsignatures and/or watermarks in the audio metering data that matchcorresponding signatures and/or watermarks in the broadcast data. Insome examples, the comparator 130 determines the amount or level ofexposure of the user to the program based on a time duration of theaudio signal sensed at the sensor 106.

In some examples, the voting data is weighted or scaled based on thelevel of exposure of the viewer to the program. A viewer of an entireprogram may have the corresponding ballot weighed more heavily than aviewer of less than the entire program. Similarly, a viewer of multipleportions of the program may have the corresponding ballot weighed moreheavily than a view who was exposed to only one portion of the program.The calculator 134 can determine a weighting score based on the level ofexposure. In examples in which there is no audio metering datacorresponding to voting data, the level of exposure may be set to nullor zero.

In some examples, the weighting score is binary: the user was exposed tothe program or a portion of the program or the user was not exposed tothe program. In some examples, the binary level is set more strictlywhere the user either saw an entire program or did not.

The tallier 138 accesses the voting data received from the user at thedata input 128. The tallier 138 modifies and/or scales the voting dataaccording to the weighting score. Thus, a user with a higher weightingscore has a more influential vote than a user with a lower weightingscore. In the binary weighting score example, the tallier 138 may givezero weight to a user not exposed to the program and full weight to auser exposed to the program. In another example with the binaryweighting score, the tallier 138 may give zero weight to a user who hasnot reached a threshold level of exposure to the program and full weightto a user who has reached the threshold level of exposure to theprogram. In other words, when the comparator 130 determines that thelevel of exposure to the program is null, the tallier 138 voids thevoting data. In yet other examples, the tallier 138 may give zero weightto a user who has not reached a threshold level of exposure to theprogram, and the tallier 138 may give scaled weight to a user who hasreached the threshold level of exposure to the program. In suchexamples, the scale of the weight is based on the level of exposurewhere more weight is given to more exposure.

The authenticator 136 authenticates the user as a viewer based on thescaled voting data. Thus, the authenticator 136 can label a user as anon-viewer based on the user not being exposed to the program or notbeing exposed to enough of the program (i.e., not being exposed to athreshold level of the program).

The tallier 138 also aggregates scaled voting data from multiple users.In some examples, the tallier 138 aggregates voting data across anaudience of the program. Thus, the tallier 138 accesses scaled votingdata from voting data received in the data input 128 from multiple userdevices 102 and voting data received at the remote center 104, forexample also via the data input 128, from people that have not votedthrough the mobile application on a user device 102. The tallier 138prepares voting results for the vote presented in the program based onthe scaled voting data of the aggregated audience. The voting resultscan be communicated via the output 140 for presentation to the producersof the program, the broadcasters of the program, the users, theaudience, the public, etc.

In some examples, the authenticator 136 determines an external influenceor level of external influence based on the scaled voting data. Forexample, the authenticator 136 analyzes all of the voting data with thescaled voting data to determine a level of voting by users not exposedto the program, not exposed to a threshold level of the program, and/oronly exposed to portions of the program. Voting by non-viewers skews theresults of the voting by the viewers. In addition, voting by thenon-viewers may result for internal influences including, for example,social media influence from posts, trends, or viral activity on socialmedia.

In some examples, the authenticator 136 determines the externalinfluence based on trends in the weighting scores. For example, a largenumber of low weighting scores or negative weighting scores couldcorrelate to a higher level of external influence. Likewise, fewer lowweighting scores than high weighting scores could correlate to a lowerlevel of external influence. Also, in some examples, the externalinfluence may be determined based on an average or mean of the weightingscores.

Also, in some examples, the authenticator 136 send instructions to theuser device 102 to perform the aforementioned activity including datacollection by instructing the user device 102 to at least trigger thesensing or collection of an audio signal based on a programming schedulethat is to identify when the program is to be broadcast; sample thesensed audio signal; decode the audio metering data from the audiosignal; accept the voting data from the user; transmit the audiometering data for access by the comparator; and transmit the voting datafor access by the tallier. Such instructions may be received by thereceiver 124 of the user device. In some examples, the instructions aresent to multiple user devices simultaneously or in succession. In someexamples, the instructions are broadcast at the beginning or prior tothe beginning of the broadcast of the program. In some examples, theinstructions are included with the installation of the mobileapplication.

Viewers may be induced to install the mobile application on theirrespective user devices 102 in order to have their ballot count (inexample in which non-viewer votes are voided) or to have their ballotsweighted more heavily (in examples in which longer exposure to a programresults in greater weight attached to a corresponding ballot and shorterexposure to a program results in a reduced weight attached to acorresponding ballot).

In some examples, the comparator 130 implements determining meansincluding means for determining the level of exposure of the user of theuser device 102 to the program. In some examples, the calculator 134implements calculating means including means for calculating theweighting score. In some examples, the tallier 138 implements tallyingmeans including means for scaling votes and tallying votes. In someexamples, the authenticator 136 implements authenticating meansincluding means for authenticating the user as a viewer of the program.One or more of the determining means, the calculating means, thetallying means, and/or the authenticating means may be implemented by aprocessor such as the processor 512 of FIG. 5 executing instructionssuch as the instructions of FIG. 4.

While an example manner of implementing the user device 102 and theremote center 104 are illustrated in FIG. 1, one or more of theelements, processes, and/or devices illustrated in FIG. 1 may becombined, divided, re-arranged, omitted, eliminated, and/or implementedin any other way. Further, the example sensor 106, the example clock108, the example scheduler 110, the example trigger 112, the examplesampler 114, the example user input 118, the example analyzer 120, theexample decoder 122, the example receiver 124, the example transmitter,the example data input 128, the example comparator 130, the examplecalculator 134, the example authenticator 136, the example tallier 138,the example output 140, and/or, more generally, the example user device102 and/or remote center 104 of FIG. 1 may be implemented by hardware,software, firmware, and/or any combination of hardware, software, and/orfirmware. Thus, for example, any of the example sensor 106, the exampleclock 108, the example scheduler 110, the example trigger 112, theexample sampler 114, the example user input 118, the example analyzer120, the example decoder 122, the example receiver 124, the exampletransmitter, the example data input 128, the example comparator 130, theexample calculator 134, the example authenticator 136, the exampletallier 138, the example output 140, the example user device 102, and/orremote center 104 could be implemented by one or more analog or digitalcircuit(s), logic circuits, programmable processor(s), programmablecontroller(s), graphics processing unit(s) (GPU(s)), digital signalprocessor(s) (DSP(s)), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)), and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example sensor 106,the example clock 108, the example scheduler 110, the example trigger112, the example sampler 114, the example user input 118, the exampleanalyzer 120, the example decoder 122, the example receiver 124, theexample transmitter, the example data input 128, the example comparator130, the example calculator 134, the example authenticator 136, theexample tallier 138, the example output 140, the example user device102, and/or remote center 104 is/are hereby expressly defined to includea non-transitory computer readable storage device or storage disk suchas a memory, a digital versatile disk (DVD), a compact disk (CD), aBlu-ray disk, etc. including the software and/or firmware. Furtherstill, the example user device 102 and/or remote center 104 of FIG. 1may include one or more elements, processes. and/or devices in additionto, or instead of, those illustrated in FIG. 1, and/or may include morethan one of any or all of the illustrated elements, processes, anddevices. As used herein, the phrase “in communication,” includingvariations thereof, encompasses direct communication and/or indirectcommunication through one or more intermediary components, and does notrequire direct physical (e.g., wired) communication and/or constantcommunication, but rather additionally includes selective communicationat periodic intervals, scheduled intervals, aperiodic intervals, and/orone-time events.

A flowchart representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the user device 102 of FIG. 1 isshown in FIG. 2. The machine readable instructions may be one or moreexecutable programs or portion(s) of an executable program for executionby a computer processor such as the processor 412 shown in the exampleprocessor platform 400 discussed below in connection with FIG. 4. Theprogram may be embodied in software stored on a non-transitory computerreadable storage medium such as a CD-ROM, a floppy disk, a hard drive, aDVD, a Blu-ray disk, or a memory associated with the processor 412, butthe entire program and/or parts thereof could alternatively be executedby a device other than the processor 412 and/or embodied in firmware ordedicated hardware. Further, although the example program is describedwith reference to the flowchart illustrated in FIG. 2, many othermethods of implementing the example user device 102 may alternatively beused. For example, the order of execution of the blocks may be changed,and/or some of the blocks described may be changed, eliminated, orcombined. Additionally or alternatively, any or all of the blocks may beimplemented by one or more hardware circuits (e.g., discrete and/orintegrated analog and/or digital circuitry, an FPGA, an ASIC, acomparator, an operational-amplifier (op-amp), a logic circuit, etc.)structured to perform the corresponding operation without executingsoftware or firmware.

A flowchart representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the remote center 104 of FIG. 1 isshown in FIG. 3. The machine readable instructions may be one or moreexecutable programs or portion(s) of an executable program for executionby a computer processor such as the processor 512 shown in the exampleprocessor platform 500 discussed below in connection with FIG. 5. Theprogram may be embodied in software stored on a non-transitory computerreadable storage medium such as a CD-ROM, a floppy disk, a hard drive, aDVD, a Blu-ray disk, or a memory associated with the processor 512, butthe entire program and/or parts thereof could alternatively be executedby a device other than the processor 512 and/or embodied in firmware ordedicated hardware. Further, although the example program is describedwith reference to the flowchart illustrated in FIG. 3, many othermethods of implementing the example remote center 104 may alternativelybe used. For example, the order of execution of the blocks may bechanged, and/or some of the blocks described may be changed, eliminated,or combined. Additionally or alternatively, any or all of the blocks maybe implemented by one or more hardware circuits (e.g., discrete and/orintegrated analog and/or digital circuitry, an FPGA, an ASIC, acomparator, an op-amp, a logic circuit, etc.) structured to perform thecorresponding operation without executing software or firmware.

In some examples one or more elements of the instructions of FIG. 2 andthe instructions of FIG. 3 may be combined or rearranged. For example,the user device 102 may perform one or more of the instructions of FIG.3. In addition, the remote center 104 may perform one or more of theinstructions of FIG. 2.

The machine readable instructions described herein may be stored in oneor more of a compressed format, an encrypted format, a fragmentedformat, a packaged format, etc. Machine readable instructions asdescribed herein may be stored as data (e.g., portions of instructions,code, representations of code, etc.) that may be utilized to create,manufacture, and/or produce machine executable instructions. Forexample, the machine readable instructions may be fragmented and storedon one or more storage devices and/or computing devices (e.g., servers).The machine readable instructions may require one or more ofinstallation, modification, adaptation, updating, combining,supplementing, configuring, decryption, decompression, unpacking,distribution, reassignment, etc. in order to make them directly readableand/or executable by a computing device and/or other machine. Forexample, the machine readable instructions may be stored in multipleparts, which are individually compressed, encrypted, and stored onseparate computing devices, wherein the parts when decrypted,decompressed, and combined form a set of executable instructions thatimplement a program such as that described herein. In another example,the machine readable instructions may be stored in a state in which theymay be read by a computer, but require addition of a library (e.g., adynamic link library (DLL)), a software development kit (SDK), anapplication programming interface (API), etc. in order to execute theinstructions on a particular computing device or other device. Inanother example, the machine readable instructions may need to beconfigured (e.g., settings stored, data input, network addressesrecorded, etc.) before the machine readable instructions and/or thecorresponding program(s) can be executed in whole or in part. Thus, thedisclosed machine readable instructions and/or corresponding program(s)are intended to encompass such machine readable instructions and/orprogram(s) regardless of the particular format or state of the machinereadable instructions and/or program(s) when stored or otherwise at restor in transit.

As mentioned above, the example processes of FIGS. 2 and 3 may beimplemented using executable instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory, and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media.

“Including” and “comprising” (and all forms and tenses thereof) are usedherein to be open ended terms. Thus, whenever a claim employs any formof “include” or “comprise” (e.g., comprises, includes, comprising,including, having, etc.) as a preamble or within a claim recitation ofany kind, it is to be understood that additional elements, terms, etc.may be present without falling outside the scope of the correspondingclaim or recitation. As used herein, when the phrase “at least” is usedas the transition term in, for example, a preamble of a claim, it isopen-ended in the same manner as the term “comprising” and “including”are open ended. The term “and/or” when used, for example, in a form suchas A, B, and/or C refers to any combination or subset of A, B, C such as(1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) Bwith C, and (7) A with B and with C. As used herein in the context ofdescribing structures, components, items, objects and/or things, thephrase “at least one of A and B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. Similarly, as used herein in the contextof describing structures, components, items, objects and/or things, thephrase “at least one of A or B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. As used herein in the context ofdescribing the performance or execution of processes, instructions,actions, activities and/or steps, the phrase “at least one of A and B”is intended to refer to implementations including any of (1) at leastone A, (2) at least one B, and (3) at least one A and at least one B.Similarly, as used herein in the context of describing the performanceor execution of processes, instructions, actions, activities and/orsteps, the phrase “at least one of A or B” is intended to refer toimplementations including any of (1) at least one A, (2) at least one B,and (3) at least one A and at least one B.

The program 200 of FIG. 2 may operate via the user device 102 that hasthe mobile application for viewer authentication installed as describedabove. The mobile application includes a schedule of broadcastprogramming, for example received by or gathered by the scheduler 110prior to the user operating the program 200 of FIG. 2. The user input118 of the user device 102 receives a program selection from a userindicating what contest programs the user intends to view, intends tocast ballots for, or otherwise has interest (block 202).

Based on a schedule for the mobile application developed by the clock108 and the scheduler 110 in accordance with the contest programsselected by the user, the trigger 112 triggers or begins the collectionof sensed audio signals by the sensor 106 (block 204). For example, thesensor 106 collects audio signals sensed from the environment of theuser device 102. The sensor 106 gathers audio signals from the contestprogram when the user device 102 is located near a television, computer,tablet, or other source presenting the contest program.

The sampler 114 samples the audio signal (block 206) to transform thesensed audio signal into a digital signal and/or frequency componentsfor further processing. The analyzer 120 analyzes the sampled audiosignals to extract audio metering data including signature(s) and/orwatermark(s) (block 208). In some examples, the analyzer 120 generatessignatures from the sensed audio signals, and in other examples, theanalyzer 120 decodes the sensed audio signals to detect watermarks inthe sensed audio signals. The audio metering data provides evidence ofthe programming presented in the environment of the user device 102. Thedatabase 116 stores or holds the audio metering data in a buffer in someexamples (block 210).

When or after a user is prompted to vote during the broadcast of thecontest program, the user input 118 receives the vote or multiple votes,which are stored in the database 116 as voting data (block 212).

The transmitter 126 transmits the audio metering data (the signature(s)and/or watermark(s)) and the voting data to the remote center 104 foranalysis and tallying (block 214). The program 200 implemented by theuser device 102 then ends. In some examples, the program 200 isimplemented multiple times where the user input 118 receives anotherselection of programming from the user (block 202) and/or where the userhas already selected multiple programs, and the trigger 112 triggerscollection of audio signals based on one of the other selected programs(block 204).

The program 300 of FIG. 3 may operate via the remote center 104. In someexamples, the program 300 of FIG. 3 includes the authenticator 136sending instructions to the user device 102 (or multiple user devices102) to perform the program 200 of FIG. 2 (block 302). The instructionsto the user device 102 prompt the collection of audio metering data andvoting data.

The comparator 130 accesses audio metering data received by the datainput 128 of the remote center 104 from the user device 104 (block 304).The comparator also accesses broadcast data representative of a programthat is received in the library 132 (block 306). The broadcast dataincludes, for examples, schedules for contest programs, referencewatermarks, and/or reference signatures. The comparator 130 performs acomparison of the audio metering data and the broadcast data (block308).

The comparator 130 determines a level of exposure of the user of theuser device 102 to the program based on the comparison of the audiometering data and the broadcast data (block 310). In some examples, thecomparator 130 determines the amount or level of exposure of the user tothe program based on the amount of signatures and/or watermarks in theaudio metering data that match corresponding signatures and/orwatermarks in the broadcast data and/or based on a time duration of theaudio signal sensed at the sensor 106. In other examples, as disclosedabove, the analyzer 120 of the user device 102 performs a comparison ofthe audio metering data and the broadcast data and determines a level ofexposure of the user of the user device 102 to the program based on thecomparison of the audio metering data and the broadcast data.

The calculator 134 determines a weighting score based on the level ofexposure (block 312). The weighting score is used to scale the votingdata based on the level of exposure of the viewer to the program.Viewers of a program or viewers of a relatively higher portions of aprogram may have the corresponding ballot or vote weighed more heavilythan a non-viewer or a viewer of a relatively lower portion of theprogram.

The tallier 138 accesses the voting data received from the user at thedata input 128 (block 314). The tallier 138 scales the voting dataaccording to the weighting score (block 316).

Based on the comparison of the audio metering data and the broadcastdata, the comparator 130 determines if the user device 102 was exposedto the broadcast program identified by the broadcast data (block 318).In other examples, the analyzer 120 of the user device 102 determines ifthe user device 102 was exposed to the broadcast program identified bythe broadcast data.

In some examples, the comparator 130 determines that the user was notexposed to the broadcast program if the audio metering data provided bythe user device does not match a program identified by the broadcastdata. In other examples, the comparator 130 determines that the user wasnot exposed to the broadcast program if there is no audio metering datacorresponding to voting data. When the comparator 130 determines thatthe user was not exposed to the broadcast program, the authenticator 136identifies the user or voter as a non-viewer (block 320). Also, asdisclosed above, in some examples, the comparator 130 determines a levelof exposure, and the authenticator 136 identifies the user or voter as anon-viewer if the level of exposure does not meet a threshold level ofexposure. The threshold level may be set based on time and also may beset in term of a particular number of minutes of exposure to the programor in terms of a particular percentage of exposure of the programrelative to the overall length of the program. If the user has beenidentified as a non-viewer, the tallier 138 modifies the voting data forthat user (block 322). In some examples, the modification includesvoiding the voting data for that user. In other examples, the non-viewervoting data is not voided but, rather, the modification includesreducing the voting data to a diminished clout or impact based on alower weight assigned to the voting data due to a lack of matchingbetween the audio metering data and broadcast data and/or a low level ofexposure that fails to meet the threshold.

Returning to block 318, in some examples, the comparator 130 determinesthat the user was exposed to the broadcast program if the audio meteringdata provided by the user device matches a program identified by thebroadcast data. When the comparator 130 determines that the user wasexposed to the broadcast program, the authenticator 136 identifies orauthenticates the user or voter as a viewer (block 324). Also, asdisclosed above, in some examples, the comparator 130 determines a levelof exposure, and the authenticator 136 authenticates the user or voteras a viewer if the level of exposure meets a threshold level such, asfor example, the threshold levels disclosed above. In some examples, theauthenticator 136 authenticates the user of the user device 102 as aviewer based on the scaled voting data.

The tallier 138 aggregates or tallies scaled voting data from multipleusers (block 326). In some examples, the tallied voting data includesvoting data for viewers. In some examples, the tallied voting data isscaled based on user exposure to the program. Also, in some examples,the non-viewer voting data is excluded, while in other examples thenon-viewer voting data is included with decreased weight. The tallier138 prepares and reports voting results for the vote presented in theprogram based on the scaled voting data of the aggregated or talliedvoting data (block 328).

In some examples, the authenticator 136 determines an external influenceor level of external influence based on the scaled voting data (block330). The external influence may be the result of social media activitythat prompts people to enter votes without viewing the program. Theauthenticator 136 can analyze the raw voting data, the scaled votingdata, and any identifications of non-viewers to determine a level ofvoting by non-viewers and/or underexposed viewers, which are users notexposed to a threshold level of the program and/or only exposed toportions of the program.

FIG. 4 is a block diagram of an example processor platform 400structured to execute the instructions of FIG. 2 to implement the userdevice 102 of FIG. 1. The processor platform 400 can be, for example, aserver, a personal computer, a workstation, a self-learning machine(e.g., a neural network), a mobile device (e.g., a cell phone, a smartphone, a tablet such as an iPad™), a personal digital assistant (PDA),an Internet appliance, a DVD player, a CD player, a digital videorecorder, a Blu-ray player, a gaming console, a personal video recorder,a set top box, a headset, or other wearable device, or any other type ofcomputing device.

The processor platform 400 of the illustrated example includes aprocessor 412. The processor 412 of the illustrated example is hardware.For example, the processor 412 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor 412 implements the sensor 106, the clock108, the scheduler 110, the trigger 112, the sampler 114, the userinput, the analyzer 120, the decoder 122, the receiver 124, and thetransmitter 126.

The processor 412 of the illustrated example includes a local memory 413(e.g., a cache). The processor 412 of the illustrated example is incommunication with a main memory including a volatile memory 414 and anon-volatile memory 416 via a bus 418. The volatile memory 414 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory(RDRAM®), and/or any other type of random access memory device. Thenon-volatile memory 416 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 414, 416is controlled by a memory controller.

The processor platform 400 of the illustrated example also includes aninterface circuit 420. The interface circuit 420 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 422 are connectedto the interface circuit 420. The input device(s) 422 permit(s) a userto enter data and/or commands into the processor 412. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint, and/or a voicerecognition system.

One or more output devices 424 are also connected to the interfacecircuit 420 of the illustrated example. The output devices 424 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printer,and/or speaker. The interface circuit 420 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chip,and/or a graphics driver processor.

The interface circuit 420 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 426. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 400 of the illustrated example also includes oneor more mass storage devices 428 for storing software and/or data.Examples of such mass storage devices 428 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives.

The machine executable instructions 432 of FIG. 2 may be stored in themass storage device 428, in the volatile memory 414, in the non-volatilememory 416, and/or on a removable non-transitory computer readablestorage medium such as a CD or DVD.

FIG. 4 is a block diagram of an example processor platform 500structured to execute the instructions of FIG. 3 to implement the remotecenter 104 of FIG. 1. The processor platform 500 can be, for example, aserver, a personal computer, a workstation, a self-learning machine(e.g., a neural network), a mobile device (e.g., a cell phone, a smartphone, a tablet such as an iPad™), a PDA, an Internet appliance, or anyother type of computing device.

The processor platform 50 of the illustrated example includes aprocessor 512. The processor 512 of the illustrated example is hardware.For example, the processor 512 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor 512 implements the data input 128, thecomparator 130, the calculator 134, the authenticator 138, the tallier138, and the output 140.

The processor 512 of the illustrated example includes a local memory 513(e.g., a cache). The processor 512 of the illustrated example is incommunication with a main memory including a volatile memory 514 and anon-volatile memory 516 via a bus 518. The volatile memory 514 may beimplemented by SDRAM, DRAM, RDRAM®, and/or any other type of randomaccess memory device. The non-volatile memory 516 may be implemented byflash memory and/or any other desired type of memory device. Access tothe main memory 514, 516 is controlled by a memory controller.

The processor platform 500 of the illustrated example also includes aninterface circuit 520. The interface circuit 520 may be implemented byany type of interface standard, such as an Ethernet interface, a USB, aBluetooth® interface, an NFC interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 522 are connectedto the interface circuit 520. The input device(s) 522 permit(s) a userto enter data and/or commands into the processor 512. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint, and/or a voicerecognition system.

One or more output devices 524 are also connected to the interfacecircuit 520 of the illustrated example. The output devices 424 can beimplemented, for example, by display devices (e.g., LED(s), OLED(s),LCD(s), a CRT display, an IPS, a touchscreen, etc.), a tactile outputdevice, a printer, and/or speaker. The interface circuit 520 of theillustrated example, thus, typically includes a graphics driver card, agraphics driver chip, and/or a graphics driver processor.

The interface circuit 520 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 526. The communication canbe via, for example, an Ethernet connection, a DSL connection, atelephone line connection, a coaxial cable system, a satellite system, aline-of-site wireless system, a cellular telephone system, etc.

The processor platform 500 of the illustrated example also includes oneor more mass storage devices 528 for storing software and/or data.Examples of such mass storage devices 528 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and DVD drives.

The machine executable instructions 532 of FIG. 3 may be stored in themass storage device 528, in the volatile memory 514, in the non-volatilememory 516, and/or on a removable non-transitory computer readablestorage medium such as a CD or DVD.

In some examples, one or more elements of the processor platform 400 ofFIG. 4 may appear alternatively or additionally in the processorplatform 500 of FIG. 5. Likewise, in some examples, one or more elementsof the processor platform 500 of FIG. 5 may appear alternatively oradditionally in the processor platform 400 of FIG. 4. In other words,some elements of the user device 102 may also be included or mayalternatively be included in the remote center 104 and vice versa.

From the foregoing, it will be appreciated that example systems,methods, apparatus, and articles of manufacture have been disclosed thatauthenticate viewers of broadcast contest programs. These techniques canbe used to confirm that voting in a competition presented in a broadcastcontest program originates from voters who actually viewed the programor, in some examples, that viewers of the program have votes that aremore heavily weighted than non-viewers or underexposed viewers. Inaddition, the techniques disclosed herein can be used to determine thelevel of external influence such as the influence produced by socialmedia activity. In addition the techniques disclosed herein arebeneficial to broadcasters because the viewer authentication disclosedherein can be used to give more confidence in the voting results andreduce accusations of rigged or unfair competition.

Disclosed herein are apparatus, systems, articles of manufacture, andmethods for viewer authentication. An example system to authenticate aviewer includes a comparator to access audio metering data received froma user device and determine a level of exposure of a user of the userdevice to a program based on the audio metering data. The example systemalso includes a calculator to determine a weighting score based on thelevel of exposure. In addition, the example system includes a tallier toaccess voting data received from the user device for a ballot presentedin the program and scale the voting data based on the weighting score.

In some examples, the system further includes an authenticator toauthenticate the user as a viewer of the program based on the scaledvoting data.

In some examples, the weighting score is binary.

In some examples, when the comparator determines that the level ofexposure is null, the tallier is to void the voting data, and theauthenticator is to identify the user as a non-viewer.

In some examples, the tallier is to aggregate scaled voting data formultiple users and prepare voting results for the ballot presented inthe program based on the scaled voting data. In such examples, theauthenticator is to determine an external influence based on the scaledvoting data.

In some examples, the external influence includes social mediainfluence.

In some examples, the level of exposure is based on a duration of theaudio metering data.

In some examples, the audio metering data includes audio signatures.

In some examples, the audio metering data includes audio watermarks.

In some examples, wherein the authenticator is to send instructions tothe user device to: trigger collection of the audio metering data basedon a programming schedule that is to identify when the program is to bebroadcast; sample a sensed audio signal when the collection of the audiometering data is triggered; determine the audio metering data from thesensed audio signal; accept the voting data from the user; transmit theaudio metering data for access by the comparator; and transmit thevoting data for access by the tallier.

Also disclosed herein is an example non-transitory computer readablestorage medium comprising computer readable instructions that, whenexecuted, cause one or more processors to, at least: determine a levelof exposure of a user of a user device to a program based on audiometering data received from the user device; determine a weighting scorebased on the level of exposure; and access voting data received from theuser device for a ballot presented in the program; and scale the votingdata based on the weighting score.

In some examples, the instructions further cause the one or moreprocessors to authenticate the user as a viewer of the program based onthe scaled voting data.

In some examples, when the level of exposure is null, the instructionsfurther cause the one or more processors to: void the voting data; andidentify the user as a non-viewer.

In some examples, the instructions further cause the one or moreprocessors to: aggregate scaled voting data for multiple users; preparevoting results for the ballot presented in the program based on thescaled voting data; and determine an external influence based on thescaled voting data.

In some examples, the instructions further cause the one or moreprocessors to send instructions to the user device to: triggercollection of the audio metering data based on a programming schedulethat is to identify when the program is to be broadcast; sample a sensedaudio signal when the collection of the audio metering data istriggered; determine the audio metering data from the sensed audiosignal; accept the voting data from the user; transmit the audiometering data for access by the one or more processors; and transmit thevoting data for access by the one or more processors.

An example system to authenticate a viewer is disclosed. The examplesystem includes means for determining a level of exposure of a user of auser device to a program based on audio metering data received from theuser device and means for calculating a weighting score based on thelevel of exposure. The example system also includes means for tallyingvotes. In this example, the means for tallying votes is to: accessvoting data received from the user device for a ballot presented in theprogram; and scale the voting data based on the weighting score.

In some examples, the system further includes means for authenticatingthe user as a viewer of the program based on the scaled voting data.

In some examples, when the means for determining determines that thelevel of exposure is null, the means for tallying is to void the votingdata, and the means for authenticating is to identify the user as anon-viewer.

In some examples, the means for tallying is to: aggregate scaled votingdata for multiple users; and prepare voting results for the ballotpresented in the program based on the scaled voting data. In suchexamples, the means for authenticating is to determine an externalinfluence based on the scaled voting data.

In some examples, the means for authenticating is to send instructionsto the user device to: trigger collection of the audio metering databased on a programming schedule that is to identify when the program isto be broadcast; sample a sensed audio signal when the collection of theaudio metering data is triggered; determine the audio metering data fromthe sensed audio signal; accept the voting data from the user; transmitthe audio metering data for access by the comparator; and transmit thevoting data for access by the tallier.

An example method to authenticate a viewer is disclosed. The examplemethod includes accessing, by executing instructions with a processor,audio metering data received from a user device; determining, byexecuting instructions with the processor, a level of exposure of a userof the user device to a program based on the audio metering data;determining, by executing instructions with the processor, a weightingscore based on the level of exposure; accessing, by executinginstructions with the processor, voting data received from the userdevice for a ballot presented in the program; and scaling, by executinginstructions with the processor, the voting data based on the weightingscore.

In some examples, the method includes authenticating, by executinginstructions with the processor, the user as a viewer of the programbased on the scaled voting data.

In some examples, the when the level of exposure is null, the methodfurther includes: voiding, by executing instructions with the processor,the voting data; and identifying, by executing instructions with theprocessor, the user as a non-viewer.

In some examples, the method includes aggregating, by executinginstructions with the processor, scaled voting data for multiple users;preparing, by executing instructions with the processor, voting resultsfor the ballot presented in the program based on the scaled voting data;and determining, by executing instructions with the processor, anexternal influence based on the scaled voting data.

In some examples, the method includes sending, by executing instructionswith the processor, instructions to the user device to: triggercollection of the audio metering data based on a programming schedulethat is to identify when the program is to be broadcast; sample a sensedaudio signal when the collection of the audio metering data istriggered; determine the audio metering data from the sensed audiosignal; accept the voting data from the user device; transmit the audiometering data for access by the processor; and transmit the voting datafor access by the processor.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. A system comprising: means for authenticating auser of a user device as a viewer of a program, the means forauthenticating to send one or more instructions to cause the user deviceto: sample a sensed audio signal based on a programming schedule that isto identify when the program is to be broadcast; determine audiometering data from the sensed audio signal; accept voting data from theuser for a ballot presented in the program; transmit the audio meteringdata; and transmit the voting data; means for determining a level ofexposure of the user to the program based on the audio metering datareceived from the user device; and means for tallying votes, the meansfor tallying votes to: access the voting data from the user device; andscale the voting data based on the level of exposure.
 2. The system ofclaim 1, wherein the means for authenticating is to authenticate theuser as a viewer of the program based on the scaled voting data.
 3. Thesystem of claim 1, further including means for calculating a weightingscore based on the level of exposure.
 4. The system of claim 1, whereinwhen the level of exposure is null, (i) the means for tallying is tovoid the voting data, and (ii) the means for authenticating is toidentify the user as a non-viewer.
 5. The system of claim 1, wherein:the means for tallying is to: aggregate scaled voting data for multipleusers; and prepare voting results for the ballot based on the aggregatedvoting data; and the means for authenticating is to determine anexternal influence based on the aggregated voting data.
 6. The system ofclaim 5, wherein the external influence includes social media influence.7. The system of claim 1, wherein the level of exposure is based on aduration of the audio metering data.
 8. The system of claim 1, whereinthe audio metering data includes audio signatures.
 9. The system ofclaim 1, wherein the audio metering data includes audio watermarks. 10.A system to authenticate a user of a user device as a viewer of aprogram, the system comprising: memory; and processor circuitry toexecute computer readable instructions to: send one or more instructionsto cause the user device to: trigger collection of audio metering datafrom a sensed audio signal based on a programming schedule that is toidentify when the program is to be broadcast; accept voting data fromthe user for a ballot presented in the program; transmit the audiometering data; and transmit the voting data; determine a level ofexposure of the user to the program based on the audio metering datareceived from the user device; calculate a weighting score based on thelevel of exposure; and adjust the voting data based on the weightingscore.
 11. The system of claim 10, wherein the processor circuitry is toauthenticate the user as a viewer of the program based on the adjustedvoting data.
 12. The system of claim 10, wherein the processor circuitryis to: aggregate adjusted voting data for multiple users; prepare votingresults for the ballot presented in the program based on the aggregatedvoting data; and determine an external influence based on the aggregatedvoting data.
 13. The system of claim 10, wherein the level of exposureis based on a duration of the audio metering data.
 14. A methodcomprising: sending instructions to a remote user device, theinstructions to cause the user device to: collect audio metering datafrom a sensed audio signal based on a programming schedule that is toidentify when a program is to be broadcast; accept voting data from auser of the user device; and return the audio metering data and thevoting data; determining, by executing an instruction with a processor,a level of exposure of the user of the user device to the program basedon the audio metering data; determining, by executing an instructionwith the processor, a weighting score based on the level of exposure;and scaling, by executing an instruction with the processor, the votingdata based on the weighting score.
 15. The method of claim 14, furtherincluding authenticating the user as a viewer of the program based onthe scaled voting data.
 16. The method of claim 15, wherein theweighting score is binary and further including, when the level ofexposure is null: voiding the voting data; and identifying the user as anon-viewer.
 17. The method of claim 14, further including: aggregatingscaled voting data for multiple users; preparing voting results for aballot presented in the program based on the aggregated voting data; anddetermining an external influence based on the aggregated voting data.18. The method of claim 14, wherein the level of exposure is based on aduration of the audio metering data.
 19. The method of claim 14, whereinthe audio metering data includes audio signatures.
 20. The method ofclaim 14, wherein the audio metering data includes audio watermarks.